code: def _pad_mvn_with_trailing_zeros(mvn, num_zeros):
      zeros = tf.zeros([num_zeros], dtype=mvn.dtype)
      return sts_util.factored_joint_mvn(
          [
              mvn,
              mvn_diag.MultivariateNormalDiag(
                  loc=zeros, scale_diag=zeros
              ),
          ]
      )
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.bijectors import tanh
  from tensorflow_probability.python.distributions import linear_gaussian_ssm
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.sts.components.autoregressive_moving_average import AutoregressiveMovingAverageStateSpaceModel
  from tensorflow_probability.python.sts.internal import missing_values_util
  from tensorflow_probability.python.sts.internal import util
  from tensorflow_probability.python.sts.structural_time_series import Parameter
  from tensorflow_probability.python.sts.structural_time_series import StructuralTimeSeries
label_desc: Use image node_id 1 for calling a global function with example usage: _pad_mvn_with_trailing_zeros(mvn, num_zeros) and returns: sts_util